DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface List of Figures List of Tables Process . Data Graphics in R Understanding Data Preparing Data Building Models Evaluating Models Algorithms Apriori Bagging Bayes Classifier Boosting Conditional Trees Decision Trees Hierarchical Clustering Kernel Methods K-Means K-Nearest Neighbours Linear Models Logistic Regression Neural Networks Support Vector Machines Text Mining Open Products Borgelt Data Mining Suite R Rattle Weka Closed Products C4.5 Clementine Enterprise Miner Equbits Foresight GhostMiner InductionEngine ODM Statistica Data Miner TreeNet Virtual Predict Appendicies Glossary Bibliography Index

Measuring Data Distributions

We now start to explore how the data in each of the variables is distributed. This might be as simple as looking at the spread of the numeric values, or the number of entities having a specific value for a variable. Another aspect involves measuring the central tendency of data, or determining the mean and median. Yet another is a measure of the spread or variance of the data from this central tendency. We again begin with textual presentations of the distributions, and then graphical presentations.

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